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biological organs
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Conductivity, Frequency-domain analysis, Image reconstruction,
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Gong, B.,
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Krueger-Ziolek, S.,
Vauhkonen, M.,
Wolf, G.,
Mueller-Lisse, U.,
Moeller, K.,
EIT Imaging Regularization Based on Spectral Graph Wavelets,
MedImg(36), No. 9, September 2017, pp. 1832-1844.
IEEE DOI
1709
bioelectric phenomena, biological tissues,
electric impedance imaging,
wavelet transforms, wavelet transforms, Jacobian matrices,
Electricalimpedancetomography
BibRef
Liu, D.,
Khambampati, A.K.,
Du, J.,
A Parametric Level Set Method for Electrical Impedance Tomography,
MedImg(37), No. 2, February 2018, pp. 451-460.
IEEE DOI
1802
Conductivity, Image reconstruction, Inverse problems, Level set,
Lungs, Shape, Tomography, Electrical impedance tomography,
parametric level set method
BibRef
Garmatter, D.[Dominik],
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Magnetic Resonance Electrical Impedance Tomography (MREIT):
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SIIMS(11), No. 1, 2018, pp. 863-887.
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BibRef
Liu, S.,
Jia, J.,
Zhang, Y.D.,
Yang, Y.,
Image Reconstruction in Electrical Impedance Tomography Based on
Structure-Aware Sparse Bayesian Learning,
MedImg(37), No. 9, September 2018, pp. 2090-2102.
IEEE DOI
1809
Tomography, Image reconstruction, Bayes methods, Electrodes,
Voltage measurement, Conductivity, Computational modeling,
maximuma posteriori(MAP) estimation
BibRef
Leijsen, R.L.,
Brink, W.M.,
van den Berg, C.A.T.,
Webb, A.G.,
Remis, R.F.,
3-D Contrast Source Inversion-Electrical Properties Tomography,
MedImg(37), No. 9, September 2018, pp. 2080-2089.
IEEE DOI
1809
Radio frequency, Mathematical model,
Image reconstruction, Magnetic resonance imaging,
electromagnetic Green's tensor field representations
BibRef
Lee, K.,
Woo, E.J.,
Seo, J.K.,
A Fidelity-Embedded Regularization Method for Robust Electrical
Impedance Tomography,
MedImg(37), No. 9, September 2018, pp. 1970-1977.
IEEE DOI
1809
Electrodes, Conductivity, Tomography, Image reconstruction,
Voltage measurement, Jacobian matrices,
motion artifacts reduction
BibRef
Hamilton, S.J.,
Hauptmann, A.,
Deep D-Bar: Real-Time Electrical Impedance Tomography Imaging With
Deep Neural Networks,
MedImg(37), No. 10, October 2018, pp. 2367-2377.
IEEE DOI
1810
Tomography, Image reconstruction, Conductivity, Real-time systems,
Impedance, Robustness, Current measurement,
conductivity imaging
BibRef
Liu, D.,
Smyl, D.,
Du, J.,
A Parametric Level Set-Based Approach to Difference Imaging in
Electrical Impedance Tomography,
MedImg(38), No. 1, January 2019, pp. 145-155.
IEEE DOI
1901
Conductivity, Tomography, Image reconstruction,
Computational modeling, Level set, Conductivity measurement,
inverse problems
BibRef
Liu, D.,
Gu, D.,
Smyl, D.,
Deng, J.,
Du, J.,
B-Spline Level Set Method for Shape Reconstruction in Electrical
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IEEE DOI
2006
Electrical impedance tomography, B-spline level set method,
Inverse problems, Shape reconstruction
BibRef
Ren, S.,
Sun, K.,
Liu, D.,
Dong, F.,
A Statistical Shape-Constrained Reconstruction Framework for
Electrical Impedance Tomography,
MedImg(38), No. 10, October 2019, pp. 2400-2410.
IEEE DOI
1910
Shape, Lung, Image reconstruction, Computed tomography, Conductivity,
Electrical impedance tomography, lung imaging,
robust principal component analysis
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Liu, D.,
Gu, D.,
Smyl, D.,
Deng, J.,
Du, J.,
B-Spline-Based Sharp Feature Preserving Shape Reconstruction Approach
for Electrical Impedance Tomography,
MedImg(38), No. 11, November 2019, pp. 2533-2544.
IEEE DOI
1911
Tomography, Splines (mathematics), Shape, Image reconstruction,
Conductivity, Fourier series, Numerical models,
inverse problems
BibRef
Liu, D.,
Du, J.,
A Moving Morphable Components Based Shape Reconstruction Framework
for Electrical Impedance Tomography,
MedImg(38), No. 12, December 2019, pp. 2937-2948.
IEEE DOI
1912
Shape, Image reconstruction, Tomography, Topology, Level set,
Conductivity, Electrodes, Electrical impedance tomography,
inverse problems
BibRef
Jiang, Y.D.,
Soleimani, M.,
Capacitively Coupled Electrical Impedance Tomography for Brain
Imaging,
MedImg(38), No. 9, September 2019, pp. 2104-2113.
IEEE DOI
1909
Electrodes, Tomography, Impedance, Head, Conductivity,
Electrical resistance measurement,
multi-frequency time-difference imaging
BibRef
Connell, I.R.O.,
Menon, R.S.,
Shape Optimization of an Electric Dipole Array for 7 Tesla
Neuroimaging,
MedImg(38), No. 9, September 2019, pp. 2177-2187.
IEEE DOI
1909
Radio frequency, Optimization, Conductors, Shape, Head, Couplings,
Impedance, Radio-frequency arrays, RF arrays, MRI RF coils, dipoles,
shape optimization
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Liang, G.,
Ren, S.,
Dong, F.,
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2002
Dual-modality imaging, inclusion boundary reconstruction,
electrical impedance tomography,
statistical inversion
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Wei, Z.,
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2005
Tomography, Conductivity, Mathematical model, Image reconstruction,
Inverse problems, Pollution measurement, Electrodes,
convolutional neural network
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Zhang, J.,
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2006
Computed tomography, cross-gradient function,
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Zaravi, S.,
Amirfattahi, R.,
Vahdat, B.V.,
Investigation of error propagation and measurement error for 2D block
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IPRIA15(1-4)
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1603
bioelectric potentials
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Lu, L.[Lin],
Liu, L.[Lili],
Hu, C.[Chun],
Analysis of the electrical impedance tomography algorithm based on
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ICWAPR14(36-42)
IEEE DOI
1402
Electrodes
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Maimaitijiang, Y.,
Roula, M.A.,
Sobeihi, K.,
Watson, S.,
Williams, R.J.,
Griffiths, H.,
A parallel implementation of a Magnetic Induction Tomography: Image
reconstruction algorithm on the ClearSpeed Advance accelerator board,
ICIP09(1757-1760).
IEEE DOI
0911
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Isa, M.D.[Mohd Daud],
Rahmat, M.F.[Mohd Fua'ad],
Application of Digital Imaging Technique in Electrical Charge
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ICMV09(277-281).
IEEE DOI
0912
BibRef
He, S.J.[Shi-Jun],
Wang, H.X.[Hua-Xiang],
Zhou, R.Y.[Ru-Yan],
A 3D Image Reconstruction Algorithm of Electrical Capacitance
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CISP09(1-4).
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0910
BibRef
Huang, J.J.[Ji-Jer],
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The effect of electrode-skin interface model in electrical impedance
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9810
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Martin, T.,
Idier, J.,
A FEM-Based Nonlinear MAP Estimator in Electrical Impedance
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ICIP97(II: 684-687).
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9700
Shallof, A.M.,
Barber, D.C.,
Imaging the complex conductivity in electrical impedance tomography,
ICIP96(III: 543-546).
IEEE DOI
9610
BibRef
Gu, T.Y.[Tian-You],
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An experimental system for the waveform recognition of impedance
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8811
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Chapter on Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models continues in
Tomographic Image Generation, Cone-Beam, Fan-Beam, Helical, Spiral Reconstruction .